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B-TECH in Artificial Intelligence And Data Science at B. S. Abdur Rahman Crescent Institute of Science and Technology
Chengalpattu, Tamil Nadu
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About the Specialization
What is Artificial Intelligence and Data Science at B. S. Abdur Rahman Crescent Institute of Science and Technology Chengalpattu?
This Artificial Intelligence and Data Science program at B.S. Abdur Rahman Crescent Institute focuses on equipping students with advanced skills in machine learning, deep learning, data analytics, and big data technologies. It is designed to meet the escalating demand in the Indian industry for professionals capable of driving digital transformation and intelligent decision-making. The program emphasizes practical application and theoretical depth, preparing graduates for cutting-edge roles.
Who Should Apply?
This program is ideal for fresh graduates with a strong aptitude for mathematics, programming, and problem-solving, seeking entry into the rapidly expanding AI and Data Science domain. It also caters to working professionals aiming to upskill or career changers transitioning into data-driven industries. Specific prerequisites include a solid foundation in science and mathematics from their higher secondary education.
Why Choose This Course?
Graduates of this program can expect to pursue lucrative India-specific career paths such as Data Scientist, AI Engineer, Machine Learning Engineer, Business Intelligence Analyst, and Big Data Developer. Entry-level salaries in India typically range from INR 5-8 LPA, with experienced professionals earning upwards of INR 15-25+ LPA. The curriculum also aligns with certifications from leading industry platforms, enhancing professional growth trajectories in Indian companies.
Student Success Practices
Foundation Stage
Master Programming Fundamentals with Python- (Semester 1-2)
Dedicate early semesters to building a robust foundation in Python programming, which is crucial for AI and Data Science. Solve daily coding challenges and practice data structures and algorithms using platforms like HackerRank and LeetCode to enhance problem-solving skills and improve coding efficiency.
Tools & Resources
Python, Jupyter Notebook, HackerRank, LeetCode, GeeksforGeeks
Career Connection
Strong programming skills are a prerequisite for all technical roles in AI/DS, ensuring readiness for technical interviews and efficient project implementation.
Cultivate Strong Mathematical and Statistical Acumen- (Semester 1-3)
Focus on understanding the underlying mathematical and statistical concepts taught in Engineering Mathematics I & II, and Probability and Statistical Methods. These are the bedrock of most AI/ML algorithms. Utilize online courses from Coursera (e.g., ''''Mathematics for Machine Learning'''') or Khan Academy to reinforce concepts.
Tools & Resources
Coursera, Khan Academy, MIT OpenCourseWare, Textbooks on Linear Algebra and Calculus
Career Connection
A deep understanding of math and statistics enables one to grasp complex algorithms, troubleshoot models, and develop innovative solutions, crucial for advanced research and development roles.
Engage in Peer Learning and Collaborative Projects- (Semester 1-2)
Form study groups to discuss complex topics, share knowledge, and collaborate on small programming assignments or mini-projects. Participating in college-level coding clubs or hackathons helps develop teamwork, communication, and practical application skills in a competitive yet supportive environment.
Tools & Resources
GitHub, Discord/Telegram groups, College Coding Clubs, Local Hackathons
Career Connection
Collaboration and communication skills are highly valued in team-oriented corporate environments, improving project outcomes and enhancing leadership potential.
Intermediate Stage
Build a Portfolio with Practical Data Science Projects- (Semester 3-5)
Beyond lab assignments, actively seek out and complete independent projects utilizing real-world datasets from Kaggle or UCI Machine Learning Repository. Focus on applying machine learning algorithms, data visualization, and basic NLP. Document your work thoroughly on GitHub.
Tools & Resources
Kaggle, UCI ML Repository, GitHub, Scikit-learn, Matplotlib/Seaborn
Career Connection
A strong project portfolio demonstrates practical skills and initiative to recruiters, significantly boosting chances for internships and entry-level positions in Indian tech companies and startups.
Participate in AI/ML Competitions and Workshops- (Semester 4-5)
Regularly participate in online AI/ML competitions on platforms like Kaggle, Analytics Vidhya, or take part in workshops and bootcamps organized by industry experts or the college. These experiences expose you to diverse problem statements and industry best practices.
Tools & Resources
Kaggle Competitions, Analytics Vidhya, Workshop Series, Industry Webinars
Career Connection
Winning or even participating in such events adds significant value to your resume, showcases problem-solving prowess, and provides networking opportunities with industry professionals, leading to potential referrals.
Explore Database Management and Big Data Technologies- (Semester 4-5)
Gain hands-on experience with SQL for relational databases and explore NoSQL databases like MongoDB. Understand the Hadoop ecosystem and Spark framework through practical exercises. Leverage online tutorials and free tiers of cloud platforms (AWS, Azure) for initial exploration.
Tools & Resources
SQL, MongoDB, Hadoop, Apache Spark, AWS/Azure Free Tier
Career Connection
Proficiency in database and big data technologies is essential for Data Engineers and Data Scientists, enabling them to handle large datasets effectively, a critical skill in data-rich Indian enterprises.
Advanced Stage
Specialize in Deep Learning and Advanced AI Concepts- (Semester 6-7)
Delve deeper into deep learning frameworks like TensorFlow/PyTorch. Work on projects involving computer vision, natural language processing, or reinforcement learning. Consider advanced online courses or certifications in these specialized areas to gain expert-level knowledge.
Tools & Resources
TensorFlow, PyTorch, Keras, OpenCV, Udemy/Coursera Advanced ML courses
Career Connection
Specialization in advanced AI areas makes you highly desirable for research-oriented roles, AI product development, and senior Data Scientist positions in innovation-driven Indian tech firms.
Pursue Internships and Industry Projects- (Semester 6-8)
Seek out multiple internships at reputable companies, both startups and established MNCs in India, to gain invaluable industry exposure. Actively contribute to final year projects that solve real-world industry problems, ideally sponsored by companies or faculty with industry ties.
Tools & Resources
Internshala, LinkedIn, College Placement Cell, Industry Connects
Career Connection
Internships provide a direct pathway to full-time employment and offer practical experience that is highly valued by Indian employers, often leading to pre-placement offers.
Focus on Placement Preparation and Soft Skills- (Semester 7-8)
Intensively prepare for placements by practicing aptitude tests, technical interviews (data structures, algorithms, ML concepts), and behavioral interviews. Develop strong communication, presentation, and team leadership skills, which are crucial for success in the Indian corporate landscape.
Tools & Resources
Mock Interviews, Aptitude Books, Career Counseling, Toastmasters/Public Speaking Clubs
Career Connection
Holistic preparation ensures you are not only technically proficient but also possess the soft skills necessary to excel in interviews and thrive in professional roles upon graduation.
Program Structure and Curriculum
Eligibility:
- Pass in the Higher Secondary Examination (10+2) curriculum with Physics, Chemistry, and Mathematics. A minimum of 45% marks (40% for OBC, SC, ST) in aggregate for Physics, Chemistry, and Mathematics is required. English must be studied as one of the subjects.
Duration: 8 semesters / 4 years
Credits: 184 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| EN1181 | Communicative English | Foundation Course | 3 | Technical Communication, Grammar and Vocabulary, Listening and Speaking Skills, Reading Comprehension, Basic Writing Skills |
| MA1181 | Engineering Mathematics I | Foundation Course | 4 | Calculus of One Variable, Functions of Several Variables, Vector Calculus, Differential Equations, Matrices and Linear Algebra |
| PH1181 | Engineering Physics | Foundation Course | 3 | Wave Optics, Quantum Physics, Solid State Physics, Semiconductor Physics, Lasers and Fiber Optics |
| PH1182 | Engineering Physics Lab | Foundation Course | 2 | Optical Experiments, Electrical and Electronic Measurements, Thermal Physics Experiments, Semiconductor Device Characteristics, Material Properties Testing |
| CY1181 | Engineering Chemistry | Foundation Course | 3 | Water Technology, Electrochemistry, Corrosion and its Control, Polymer Chemistry, Materials Chemistry |
| CY1182 | Engineering Chemistry Lab | Foundation Course | 2 | Volumetric Analysis, Potentiometric Titration, Conductometric Titration, Spectrophotometric Analysis, Hardness of Water Determination |
| GE1181 | Problem Solving and Python Programming | Programme Core | 3 | Algorithmic Problem Solving, Python Basics, Control Flow, Functions and Modules, Data Structures in Python |
| GE1182 | Problem Solving and Python Programming Lab | Programme Core | 2 | Python Program Development, Conditional and Looping Structures, Function Implementation, List and Dictionary Operations, File Handling |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| EN1281 | Advanced Communicative English | Foundation Course | 3 | Advanced Reading Strategies, Effective Public Speaking, Group Discussions, Professional Writing, Presentation Skills |
| MA1281 | Engineering Mathematics II | Foundation Course | 4 | Laplace Transforms, Fourier Series, Partial Differential Equations, Complex Variables, Vector Spaces |
| CS1221 | Programming with C | Programme Core | 3 | C Language Fundamentals, Control Statements, Arrays and Strings, Functions and Pointers, Structures and Unions |
| CS1222 | Programming with C Lab | Programme Core | 2 | C Program Debugging, Array and String Manipulation, Pointers and Dynamic Memory Allocation, File Operations, Data Structures Implementation |
| GE1281 | Engineering Graphics | Foundation Course | 4 | Orthographic Projections, Projection of Solids, Section of Solids, Development of Surfaces, Isometric Projections |
| GE1282 | Engineering Practices Lab | Foundation Course | 2 | Carpentry and Fitting, Welding and Sheet Metal, Plumbing and Wiring, Basic Machining Operations, Electronic Circuit Assembly |
| GE1283 | Environmental Science and Engineering | Foundation Course | 3 | Ecosystems and Biodiversity, Environmental Pollution, Solid Waste Management, Sustainable Development, Environmental Protection Acts |
| AD1201 | Artificial Intelligence and Data Science Essentials | Programme Core | 3 | Introduction to AI, Problem Solving Agents, Introduction to Data Science, Data Analytics Process, Applications of AI and Data Science |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA2181 | Probability and Statistical Methods | Foundation Course | 4 | Random Variables and Distributions, Correlation and Regression, Sampling Distributions, Hypothesis Testing, Analysis of Variance |
| CS2121 | Data Structures and Algorithms | Programme Core | 3 | Array and Linked Lists, Stacks and Queues, Trees and Graphs, Searching Algorithms, Sorting Algorithms |
| CS2122 | Data Structures and Algorithms Lab | Programme Core | 2 | List and Stack Implementation, Queue and Tree Operations, Graph Traversal Algorithms, Hashing Techniques, Algorithm Efficiency Analysis |
| AD2101 | Database Management Systems | Programme Core | 3 | Relational Model, SQL Queries, Database Design, Normalization, Transaction Management |
| AD2102 | Database Management Systems Lab | Programme Core | 2 | DDL and DML Commands, Joins and Subqueries, Stored Procedures, Database Connectivity, Mini Project on Database Design |
| AD2103 | Object Oriented Programming with Java | Programme Core | 3 | Java Basics, Classes and Objects, Inheritance and Polymorphism, Exception Handling, Multithreading |
| AD2104 | Object Oriented Programming with Java Lab | Programme Core | 2 | Java Application Development, GUI Programming, JDBC Connectivity, Collections Framework, Web Application Concepts |
| AD2105 | Design and Analysis of Algorithms | Programme Core | 3 | Algorithm Analysis, Divide and Conquer, Dynamic Programming, Greedy Algorithms, Graph Algorithms |
| HS2181 | Professional Ethics | Humanities and Social Sciences | 2 | Engineering Ethics, Moral Autonomy, Risk and Safety, Professional Rights, Global Issues in Engineering |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AD2201 | Discrete Mathematics | Programme Core | 4 | Logic and Proofs, Set Theory and Functions, Combinatorics, Graph Theory, Algebraic Structures |
| AD2202 | Operating Systems | Programme Core | 3 | OS Structures, Process Management, CPU Scheduling, Memory Management, File Systems |
| AD2203 | Operating Systems Lab | Programme Core | 2 | Linux Commands, Shell Scripting, Process Creation, CPU Scheduling Simulation, Memory Allocation Techniques |
| AD2204 | Computer Architecture and Organization | Programme Core | 3 | Digital Logic Circuits, Processor Organization, Memory Hierarchy, Input/Output Organization, Pipelining |
| AD2205 | Artificial Intelligence | Programme Core | 3 | Intelligent Agents, Search Strategies, Knowledge Representation, Uncertainty Management, Machine Learning Basics |
| AD2206 | Artificial Intelligence Lab | Programme Core | 2 | Prolog/Python for AI, Search Algorithm Implementation, Knowledge Representation Exercises, Logic Programming, Simple AI Agent Development |
| AD2207 | Data Science Essentials | Programme Core | 3 | Data Collection and Preprocessing, Exploratory Data Analysis, Statistical Modeling, Data Mining Techniques, Introduction to R/Python for Data Science |
| AD2208 | Data Science Essentials Lab | Programme Core | 2 | Data Wrangling with Pandas, Data Visualization with Matplotlib/Seaborn, Statistical Analysis in Python/R, Regression Analysis, Classification Model Implementation |
| AD2209 | Software Engineering | Programme Core | 3 | Software Development Life Cycle, Requirements Engineering, Software Design, Software Testing, Project Management |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AD3101 | Machine Learning | Programme Core | 3 | Supervised Learning, Unsupervised Learning, Ensemble Methods, Model Evaluation, Feature Engineering |
| AD3102 | Machine Learning Lab | Programme Core | 2 | Scikit-learn Implementation, Regression Models, Classification Models, Clustering Algorithms, Dimensionality Reduction |
| AD3103 | Big Data Analytics | Programme Core | 3 | Introduction to Big Data, Hadoop Ecosystem, MapReduce, Spark Framework, NoSQL Databases |
| AD3104 | Big Data Analytics Lab | Programme Core | 2 | HDFS Operations, MapReduce Programming, Spark DataFrames, Hive Queries, MongoDB Operations |
| AD3105 | Computer Networks | Programme Core | 3 | Network Topologies, OSI and TCP/IP Models, Network Devices, Routing Protocols, Network Security Basics |
| AD3106 | Compiler Design | Programme Core | 3 | Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization |
| HS3181 | Constitution of India | Humanities and Social Sciences | 1 | Preamble and Fundamental Rights, Directive Principles of State Policy, Union and State Governments, Judiciary System, Constitutional Amendments |
| PE0001 | Program Elective I | Program Elective | 3 | Advanced topics in AI/Data Science, Specialized domain applications, Emerging technologies, Research frontiers, Industry-specific tools |
| RM3181 | Research Methodology | Programme Core | 2 | Research Problem Formulation, Literature Review, Research Design, Data Collection and Analysis, Report Writing |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AD3201 | Deep Learning | Programme Core | 3 | Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks, Deep Learning Frameworks |
| AD3202 | Deep Learning Lab | Programme Core | 2 | TensorFlow/PyTorch Implementation, Image Classification, Sequence Prediction, Object Detection, Model Training and Tuning |
| AD3203 | Natural Language Processing | Programme Core | 3 | Text Preprocessing, Language Models, Sentiment Analysis, Machine Translation, Information Extraction |
| AD3204 | Natural Language Processing Lab | Programme Core | 2 | NLTK/SpaCy Usage, Text Classification, Named Entity Recognition, Word Embeddings, Chatbot Development |
| GE3281 | Professional Communication | Humanities and Social Sciences | 2 | Workplace Communication, Interpersonal Skills, Technical Report Writing, Interview Skills, Negotiation Skills |
| PE0002 | Program Elective II | Program Elective | 3 | Advanced Machine Learning, Computer Vision, Reinforcement Learning, Data Warehousing, Time Series Analysis |
| PE0003 | Program Elective III | Program Elective | 3 | Applied AI, Predictive Analytics, Business Intelligence, Data Governance, IoT Analytics |
| OE0001 | Open Elective I | Open Elective | 3 | Interdisciplinary topics, Management principles, Entrepreneurship, Humanities and Arts, Societal impact of technology |
| AD3205 | Mini Project | Programme Core | 2 | Problem Identification, System Design, Implementation and Testing, Project Report Writing, Presentation Skills |
| AD3206 | Industrial Internship | Employability Enhancement Course | 1 | Industry Work Exposure, Application of Theoretical Knowledge, Professional Networking, Report and Presentation, Teamwork and Collaboration |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AD4101 | Cloud Computing | Programme Core | 3 | Cloud Service Models, Cloud Deployment Models, Virtualization, Cloud Security, AWS/Azure/GCP Services |
| AD4102 | Cloud Computing Lab | Programme Core | 2 | AWS/Azure/GCP Account Setup, EC2/VM Instance Management, S3/Blob Storage Operations, Database Services in Cloud, Cloud Function Deployment |
| AD4103 | Ethical Hacking and Cybersecurity | Programme Core | 3 | Cybersecurity Fundamentals, Network Security, Web Application Security, Malware Analysis, Ethical Hacking Techniques |
| PE0004 | Program Elective IV | Program Elective | 3 | AI in Healthcare, FinTech and AI, Cyber-Physical Systems, Bioinformatics and Data Science, Robotics and AI |
| PE0005 | Program Elective V | Program Elective | 3 | Edge Computing, Quantum Computing Principles, Blockchain and AI, Cognitive Computing, Human-Computer Interaction |
| OE0002 | Open Elective II | Open Elective | 3 | Advanced communication, Project management, Foreign language, Design thinking, Social entrepreneurship |
| AD4104 | Project Work Phase I | Programme Core | 6 | Problem Definition, Literature Survey, System Design and Architecture, Feasibility Study, Initial Implementation |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| AD4201 | Social and Web Analytics | Programme Core | 3 | Web Analytics Fundamentals, Social Media Metrics, Sentiment Analysis for Social Media, Network Analysis, E-commerce Analytics |
| AD4202 | Social and Web Analytics Lab | Programme Core | 2 | Google Analytics Implementation, Social Media Data Extraction, Web Scraping Tools, Sentiment Analysis Tools, Dashboards for Web/Social Data |
| AD4203 | Data Visualization | Programme Core | 3 | Principles of Data Visualization, Visual Encoding Techniques, Dashboard Design, Interactive Visualizations, Tools like Tableau/PowerBI |
| AD4204 | Data Visualization Lab | Programme Core | 2 | Python Plotting Libraries, R Graphics, Tableau/PowerBI Dashboard Creation, Storytelling with Data, Infographic Design |
| AD4205 | Project Work Phase II | Programme Core | 10 | Advanced System Development, Testing and Validation, Performance Optimization, Technical Documentation, Project Defense and Presentation |
